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Scientific novelty is important during the pandemic due to its critical role in generating new vaccines. Parachuting collaboration and international collaboration are two crucial channels to expand teams search activities for a broader scope of resources required to address the global challenge. Our analysis of 58,728 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pre-trained on 29 million PubMed articles, and parachuting collaboration dramatically increased after the outbreak of COVID-19, while international collaboration witnessed a sudden decrease. During the COVID-19, papers with more parachuting collaboration and internationally collaborative papers are predicted to be more novel. The findings suggest the necessity of reaching out for distant resources, and the importance of maintaining a collaborative scientific community beyond established networks and nationalism during a pandemic.
Science is built upon scholarship consensus that changes over time. This raises the question of how revolutionary theories and assumptions are evaluated and accepted into the norm of science as the setting for the next science. Using two recently pro
The new coronavirus known as COVID-19 is spread world-wide since December 2019. Without any vaccination or medicine, the means of controlling it are limited to quarantine and social distancing. Here we study the spatio-temporal propagation of the fir
The COVID-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on COVID-19 and related historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information retrieval systems over i
In this article, we conduct data mining to discover the countries, universities and companies, produced or collaborated the most research on Covid-19 since the pandemic started. We present some interesting findings, but despite analysing all availabl
The emergence of Covid-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with highly disaggregated spatial and temporal units of analysis, are a priority in this sense. Spati